class_docstr: Indexed entropy model for location-scale family of random variables.
  
  This class is a common special case of `ContinuousIndexedEntropyModel`. The
  specified distribution is parameterized with `num_scales` values of scale
  parameters. An element-wise location parameter is handled by shifting the
  distributions to zero.
  
  This method is illustrated in Figure 10 of:
  > "Nonlinear Transform Coding"<br />
  > J. Ballé, P.A. Chou, D. Minnen, S. Singh, N. Johnston, E. Agustsson,
  > S.J. Hwang, G. Toderici<br />
  > https://doi.org/10.1109/JSTSP.2020.3034501
  
  Note: this only works for shift-invariant `tfpd.Distribution` objects, where
  the `loc` parameter really denotes a translation (i.e., not for the log-normal
  distribution).
docstr: Decompresses a tensor.
  
  Reconstructs the quantized tensor from bit strings produced by `compress()`.
  
  Args:
    strings: `tf.Tensor` containing the compressed bit strings.
    scale_indexes: `tf.Tensor` indexing the scale parameter for each output
      element.
    loc: `None` or `tf.Tensor`. If `None`, the location parameter for all
      output elements is assumed to be zero. Otherwise, specifies the location
      parameter for each output element. Must have the same shape as
      `scale_indexes`.
  
  Returns:
    A `tf.Tensor` of the same shape as `scale_indexes`.
docstr_tok: ["Decompresses","a","tensor",".","Reconstructs","the","quantized","tensor","from","bit","strings","produced","by","`","compress","(",")","`",".","Args",":","strings",":","`","tf.Tensor","`","containing","the","compressed","bit","strings",".","scale_indexes",":","`","tf.Tensor","`","indexing","the","scale","parameter","for","each","output","element",".","loc",":","`","None","`","or","`","tf.Tensor","`",".","If","`","None","`",",","the","location","parameter","for","all","output","elements","is","assumed","to","be","zero",".","Otherwise",",","specifies","the","location","parameter","for","each","output","element",".","Must","have","the","same","shape","as","`","scale_indexes","`",".","Returns",":","A","`","tf.Tensor","`","of","the","same","shape","as","`","scale_indexes","`","."]
code: def decompress(self, strings, scale_indexes, loc=None):
      """Decompresses a tensor.
  
      Reconstructs the quantized tensor from bit strings produced by `compress()`.
  
      Args:
        strings: `tf.Tensor` containing the compressed bit strings.
        scale_indexes: `tf.Tensor` indexing the scale parameter for each output
          element.
        loc: `None` or `tf.Tensor`. If `None`, the location parameter for all
          output elements is assumed to be zero. Otherwise, specifies the location
          parameter for each output element. Must have the same shape as
          `scale_indexes`.
  
      Returns:
        A `tf.Tensor` of the same shape as `scale_indexes`.
      """
      values = super().decompress(strings, scale_indexes)
      if loc is not None:
          values += loc
      return values
  
imports: import tensorflow
  from tensorflow_compression.python.entropy_models import continuous_base
  from tensorflow_compression.python.ops import gen_ops
  from tensorflow_compression.python.ops import math_ops
  from tensorflow_compression.python.ops import round_ops
label_desc: Use image node_id 5 for calling the LocationScaleIndexedEntropyModel obj's underlying member method code with example usage: obj.decompress(strings, scale_indexes, loc) and returns: values